Top beverage brands combine mobile task management for teams with the fastest and most accurate image recognition platform to improve sales. Teams reduce audit time, increase display compliance, improve accuracy, and optimize rep performance with computer vision and machine learning to give corporate leaders unprecedented visibility to their market position in real-time.
On sales routes, reps capture live photos of cold boxes, cold vaults, coolers, and cocktail menus on smartphones or tablets. Our trained machine learning algorithms then quickly detect assets, identify products, and segment categories found within the image. Granular insights on brand, category, supplier, SKU count, assortment, and percentage share are processed, and analytics are returned to reps on-device in under 2 minutes. Sales leaders can direct actions based on image results--creating a real-time optimizer in the market and a seamless rep experience in one app.
Our customers have reduced audit times by more than 50%--visiting more accounts in less time, improving contract compliance worth tens of millions of dollars in incremental sales, and self-funding the models and technology with a demonstrable ROI.
GoSpotCheck’s industry-leading Image Recognition models can be trained for coolers and cold vaults at off-premise or small format stores, or on cocktail menus at on-premise bars and restaurants. Our image recognition models are trained by capturing real product images in-market, which are automatically tagged by our proprietary cloud-based machine-learning algorithms. Human auditors based in Denver, CO, help ensure that new or unknown products are tagged correctly when first identified, helping to continuously train, improve, and strengthen the model.
Sales teams use photos processed with image recognition to streamline field audits and capture valuable market intelligence for corporate strategies. Often, teams need to gather contextual data in addition to images to produce holistic insights, so we designed our system to quickly capture data in digital surveys integrated with image recognition to produce a seamless rep experience and unparalleled analytics in a single mobile application.
Once enabled, sales leaders can easily create Image Recognition tasks within GoSpotCheck missions to be deployed to field teams using the mobile app. Capturing a photo for Image Recognition is as easy as point and shoot--if you know how to use a camera, then you know how to use Image Recognition from GoSpotCheck.
Before you even capture a photo, our machine learning models will kick in to provide guidance on how to capture the best possible image. Users get real-time feedback if the photo has quality problems like blurriness, glare spots, or a closed cooler door--improving the quality of data returning to headquarters from the field.
After a high-quality image is captured, our machine learning models go to work. They automatically segment the image to quickly identify relevant products or menu items and return SKU-level data to users on their devices in seconds.
When using GoSpotCheck’s Image Recognition, you can expect on-device reporting results in 2-minutes or less with 98% average detection accuracy on trained UPCs. This is the fastest turnaround time with the most accurate product recognition for on-device results in the market, made possible by the robust tagging system and highly-performant machine learning models we’ve developed. Photos and Image Recognition data flow seamlessly into GoSpotCheck’s reporting dashboards so you can aggregate and analyze the data and integrate it with other systems of record. SKU-level tag data can enrich custom reports in our Insights platform, or be exported in bulk through our API. Plus, all your photos can be easily sorted, filtered, and exported in the GoSpotCheck PhotoWorks library--the industry’s top photo reporting platform.
GoSpotCheck’s industry-leading Image Recognition models can be trained for coolers and cold vaults at off-premise or small format stores, or on cocktail menus at on-premise bars and restaurants. Our image recognition models are trained by capturing real product images in-market, which are automatically tagged by our proprietary cloud-based machine-learning algorithms. Human auditors based in Denver, CO, help ensure that new or unknown products are tagged correctly when first identified, helping to continuously train, improve, and strengthen the model.
Sales teams use photos processed with image recognition to streamline field audits and capture valuable market intelligence for corporate strategies. Often, teams need to gather contextual data in addition to images to produce holistic insights, so we designed our system to quickly capture data in digital surveys integrated with image recognition to produce a seamless rep experience and unparalleled analytics in a single mobile application.
Once enabled, sales leaders can easily create Image Recognition tasks within GoSpotCheck missions to be deployed to field teams using the mobile app. Capturing a photo for Image Recognition is as easy as point and shoot--if you know how to use a camera, then you know how to use Image Recognition from GoSpotCheck.
Before you even capture a photo, our machine learning models will kick in to provide guidance on how to capture the best possible image. Users get real-time feedback if the photo has quality problems like blurriness, glare spots, or a closed cooler door--improving the quality of data returning to headquarters from the field.
After a high-quality image is captured, our machine learning models go to work. They automatically segment the image to quickly identify relevant products or menu items and return SKU-level data to users on their devices in seconds.
When using GoSpotCheck’s Image Recognition, you can expect on-device reporting results in 2-minutes or less with 98% average detection accuracy on trained UPCs. This is the fastest turnaround time with the most accurate product recognition for on-device results in the market, made possible by the robust tagging system and highly-performant machine learning models we’ve developed. Photos and Image Recognition data flow seamlessly into GoSpotCheck’s reporting dashboards so you can aggregate and analyze the data and integrate it with other systems of record. SKU-level tag data can enrich custom reports in our Insights platform, or be exported in bulk through our API. Plus, all your photos can be easily sorted, filtered, and exported in the GoSpotCheck PhotoWorks library--the industry’s top photo reporting platform.
GoSpotCheck’s industry-leading Image Recognition models can be trained for coolers and cold vaults at off-premise or small format stores, or on cocktail menus at on-premise bars and restaurants. Our image recognition models are trained by capturing real product images in-market, which are automatically tagged by our proprietary cloud-based machine-learning algorithms. Human auditors based in Denver, CO, help ensure that new or unknown products are tagged correctly when first identified, helping to continuously train, improve, and strengthen the model.
Sales teams use photos processed with image recognition to streamline field audits and capture valuable market intelligence for corporate strategies. Often, teams need to gather contextual data in addition to images to produce holistic insights, so we designed our system to quickly capture data in digital surveys integrated with image recognition to produce a seamless rep experience and unparalleled analytics in a single mobile application.
Once enabled, sales leaders can easily create Image Recognition tasks within GoSpotCheck missions to be deployed to field teams using the mobile app. Capturing a photo for Image Recognition is as easy as point and shoot--if you know how to use a camera, then you know how to use Image Recognition from GoSpotCheck.
Before you even capture a photo, our machine learning models will kick in to provide guidance on how to capture the best possible image. Users get real-time feedback if the photo has quality problems like blurriness, glare spots, or a closed cooler door--improving the quality of data returning to headquarters from the field.
After a high-quality image is captured, our machine learning models go to work. They automatically segment the image to quickly identify relevant products or menu items and return SKU-level data to users on their devices in seconds.
When using GoSpotCheck’s Image Recognition, you can expect on-device reporting results in 2-minutes or less with 98% average detection accuracy on trained UPCs. This is the fastest turnaround time with the most accurate product recognition for on-device results in the market, made possible by the robust tagging system and highly-performant machine learning models we’ve developed. Photos and Image Recognition data flow seamlessly into GoSpotCheck’s reporting dashboards so you can aggregate and analyze the data and integrate it with other systems of record. SKU-level tag data can enrich custom reports in our Insights platform, or be exported in bulk through our API. Plus, all your photos can be easily sorted, filtered, and exported in the GoSpotCheck PhotoWorks library--the industry’s top photo reporting platform.
98%+ UPC Detection Accuracy *
~ 2-Minute On-Device Reporting **
* Accuracy against TRAINED UPCs (ie products that have been trained in our Machine Learning system)
** Dependent on connectivity strength
Cold Vault
Cooler
Shelf
Menu - Cocktail
Menu - Wine
Back Bar
Pricing Detection
iOS - Phones + Tablets
Android - Phones + Tablets
Currently not supported on Windows 10
English
French
Spanish
Additionally, missions can be written in any language
GoSpotCheck customers combine the power of mobile task management with image recognition to optimize these and other business processes to improve field sales performance: